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Himabindu Lakkaraju

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

54

Venues

19

Active years

2011–2026

Best venue rank

A*

Where they publish

Papers

54 indexed papers, newest first.

YearVenueTitleAuthors
2026ACLGeneralizing Trust: Weak-to-Strong Trustworthiness in Language Models.Lillian Sun, Martin Pawelczyk, Zhenting Qi, Aounon Kumar, Himabindu Lakkaraju
2026ACLHow Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior.Zidi Xiong, Yuping Lin, Wenya Xie, Pengfei He, Zirui Liu, Jiliang Tang, Himabindu Lakkaraju, Zhen Xiang
2026EACLEvaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders.Aaron J. Li, Suraj Srinivas, Usha Bhalla, Himabindu Lakkaraju
2025ICLRMore RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness.Aaron Jiaxun Li, Satyapriya Krishna, Himabindu Lakkaraju
2025ICLRQuantifying Generalization Complexity for Large Language Models.Zhenting Qi, Hongyin Luo, Xuliang Huang, Zhuokai Zhao, Yibo Jiang, Xiangjun Fan, Himabindu Lakkaraju, James R. Glass
2025ICLRFollow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems.Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju
2025ISITSoft Best-of-$n$ Sampling for Model Alignment.Claudio Mayrink Verdun, Alex Oesterling, Himabindu Lakkaraju, Flvio P. Calmon
2025IUICounterfactual Explanations May Not Be the Best Algorithmic Recourse Approach.Sohini Upadhyay, Himabindu Lakkaraju, Krzysztof Z. Gajos
2025NAACLOn the Impact of Fine-Tuning on Chain-of-Thought Reasoning.Elita A. Lobo, Chirag Agarwal, Himabindu Lakkaraju
2024AIESOn the Trade-offs between Adversarial Robustness and Actionable Explanations.Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2024AISTATSFair Machine Unlearning: Data Removal while Mitigating Disparities.Alex Oesterling, Jiaqi Ma, Flvio P. Calmon, Himabindu Lakkaraju
2024AISTATSQuantifying Uncertainty in Natural Language Explanations of Large Language Models.Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju
2024ICMLUnderstanding the Effects of Iterative Prompting on Truthfulness.Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju
2024ICMLIn-Context Unlearning: Language Models as Few-Shot Unlearners.Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
2024KDDThe First Workshop on AI Behavioral Science.Himabindu Lakkaraju, Qiaozhu Mei, Chenhao Tan, Jie Tang, Yutong Xie
2024NAACLConfronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications.Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju
2024NAACLA Study on the Calibration of In-context Learning.Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean P. Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade
2024UAICharacterizing Data Point Vulnerability as Average-Case Robustness.Tessa Han, Suraj Srinivas, Himabindu Lakkaraju
2023AISTATSOn the Privacy Risks of Algorithmic Recourse.Martin Pawelczyk, Himabindu Lakkaraju, Seth Neel
2023ICLRProbabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse.Martin Pawelczyk, Teresa Datta, Johannes van den Heuvel, Gjergji Kasneci, Himabindu Lakkaraju
2023ICMLOn the Impact of Algorithmic Recourse on Social Segregation.Ruijiang Gao, Himabindu Lakkaraju
2023ICMLTowards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten.Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju
2023KDDGenerative AI meets Responsible AI: Practical Challenges and Opportunities.Krishnaram Kenthapadi, Himabindu Lakkaraju, Nazneen Rajani
2023WWWTutorials at The Web Conference 2023.Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espn-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Kk-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu
2023UAIOn Minimizing the Impact of Dataset Shifts on Actionable Explanations.Anna P. Meyer, Dan Ley, Suraj Srinivas, Himabindu Lakkaraju
2022AIESFairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations.Jessica Dai, Sohini Upadhyay, Ulrich Avodji, Stephen H. Bach, Himabindu Lakkaraju
2022AIESTowards Robust Off-Policy Evaluation via Human Inputs.Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2022AISTATSProbing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
2022AISTATSExploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju
2022HCOMPA Human-Centric Perspective on Model Monitoring.Murtuza N. Shergadwala, Himabindu Lakkaraju, Krishnaram Kenthapadi
2022KDDModel Monitoring in Practice: Lessons Learned and Open Challenges.Krishnaram Kenthapadi, Himabindu Lakkaraju, Pradeep Natarajan, Mehrnoosh Sameki
2022UAIData poisoning attacks on off-policy policy evaluation methods.Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju
2021AAAIFair Influence Maximization: a Welfare Optimization Approach.Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe
2021AIESDoes Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring.Tom Shr, Sophie Hilgard, Himabindu Lakkaraju
2021CIKMTowards Reliable and Practicable Algorithmic Recourse.Himabindu Lakkaraju
2021ICMLTowards the Unification and Robustness of Perturbation and Gradient Based Explanations.Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju
2021UAITowards a unified framework for fair and stable graph representation learning.Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik
2020AIES"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations.Himabindu Lakkaraju, Osbert Bastani
2020AIESFooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods.Dylan Slack, Sophie Hilgard, Emily Jia, Sameer Singh, Himabindu Lakkaraju
2020ICMLRobust and Stable Black Box Explanations.Himabindu Lakkaraju, Nino Arsov, Osbert Bastani
2019AIESFaithful and Customizable Explanations of Black Box Models.Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Jure Leskovec
2017AAAIIdentifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration.Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz
2017AISTATSLearning Cost-Effective and Interpretable Treatment Regimes.Himabindu Lakkaraju, Cynthia Rudin
2017KDDThe Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables.Himabindu Lakkaraju, Jon M. Kleinberg, Jure Leskovec, Jens Ludwig, Sendhil Mullainathan
2016KDDInterpretable Decision Sets: A Joint Framework for Description and Prediction.Himabindu Lakkaraju, Stephen H. Bach, Jure Leskovec
2015KDDA Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes.Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani, Kecia L. Addison
2015LAKWho, when, and why: a machine learning approach to prioritizing students at risk of not graduating high school on time.Everaldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia L. Addison
2015SDMA Bayesian Framework for Modeling Human Evaluations.Himabindu Lakkaraju, Jure Leskovec, Jon M. Kleinberg, Sendhil Mullainathan
2013ICWSMWhat's in a Name? Understanding the Interplay between Titles, Content, and Communities in Social Media.Himabindu Lakkaraju, Julian J. McAuley, Jure Leskovec
2012ICDMDynamic Multi-relational Chinese Restaurant Process for Analyzing Influences on Users in Social Media.Himabindu Lakkaraju, Indrajit Bhattacharya, Chiranjib Bhattacharyya
2012WWWTEM: a novel perspective to modeling content onmicroblogs.Himabindu Lakkaraju, Hyung-Il Ahn
2011CIKMAttention prediction on social media brand pages.Himabindu Lakkaraju, Jitendra Ajmera
2011WWWSmart news feeds for social networks using scalable joint latent factor models.Himabindu Lakkaraju, Angshu Rai, Srujana Merugu
2011SDMExploiting Coherence for the Simultaneous Discovery of Latent Facets and associated Sentiments.Himabindu Lakkaraju, Chiranjib Bhattacharyya, Indrajit Bhattacharya, Srujana Merugu